Agricultural Induction Motor Direct Torque Control Using Neural Networks

In this paper, a novel approach to direct torque control to control the induction motor is presented. This method is based on the theory of the N-N algorithm. The learning arithmetic of Levenberg-Marquardt is used. The Neural Networks replace the choice of switching states. With MATLAB, the simulation is conducted, and the results show that the direct torque control system using this method has the same performance as conventional direct torque control. This motivates further research in the application of neural networks to new types of controllers in motor drive industry.